Evidence map›Paper›PMID 35385469›Full record

SynthesisPLoS computational biology2022

Optimizing clinical dosing of combination broadly neutralizing antibodies for HIV prevention.

Bryan T Mayer, Allan C deCamp, Yunda Huang, Joshua T Schiffer, Raphael Gottardo, Peter B Gilbert, Daniel B Reeves

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.7field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 25 citations in OpenAlex.

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  16. The potential of broadly neutralizing antibodies for HIV prevention.Journal of the International AIDS Society · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Bryan T MayerVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.ORCID 0000-0003-2258-5276
Allan C deCampVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.ORCID 0000-0003-1404-4322
Yunda HuangVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.ORCID 0000-0003-1546-6172
Joshua T SchifferVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.ORCID 0000-0002-2598-1621
Raphael GottardoVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.ORCID 0000-0002-3867-0232
Peter B GilbertVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
Daniel B ReevesVaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.ORCID 0000-0001-5684-9538
Fred Hutch Cancer Center · USUniversity of Washington · US

Funding

LOC: HIV Vaccine Trials NetworkUM1AI068614 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Dan H. Barouch, Lawrence Corey · 2011 to 2026
$1175.6M
SDMC: HIV Vaccine Trials NetworkUM1AI068635 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Peter B. Gilbert, Yunda Huang · 2011 to 2026
$385.9M
Cell and Gene Therapy for HIV CureUM1AI126623 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI JEROME, KEITH R, KIEM, HANS-PETER · 2016 to 2020
$24.2M
Statistical Methods in HIV Vaccine Efficacy TrialsR37AI054165 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Peter B. Gilbert · 2010 to 2026
$6.7M
Mathematical modeling of optimal therapeutic combinations for HIV cureR01AI150500 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI SCHIFFER, JOSHUA TISDELL · 2020 to 2024
$2.3M
Simulating persistence and elimination of the HIV reservoirK25AI155224 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI REEVES, DANIEL · 2020 to 2024
$581k
NIAID NIH HHS K25 AI155224NIAID NIH HHS R01 AI150500NIAID NIH HHS R37 AI054165NIAID NIH HHS UM1 AI068614NIAID NIH HHS UM1 AI068635NIAID NIH HHS UM1 AI126623
6 · The paper itself

Abstract

Broadly neutralizing antibodies (bNAbs) are promising agents to prevent HIV infection and achieve HIV remission without antiretroviral therapy (ART). As with ART, bNAb combinations are likely needed to cover HIV's extensive diversity. Not all bNAbs are identical in terms of their breadth, potency, and in vivo longevity (half-life). Given these differences, it is important to optimally select the composition, or dose ratio, of combination bNAb therapies for future clinical studies. We developed a model that synthesizes 1) pharmacokinetics, 2) potency against a wide HIV diversity, 3) interaction models for how drugs work together, and 4) correlates that translate in vitro potency to clinical protection. We found optimization requires drug-specific balances between potency, longevity, and interaction type. As an example, tradeoffs between longevity and potency are shown by comparing a combination therapy to a bi-specific antibody (a single protein merging both bNAbs) that takes the better potency but the worse longevity of the two components. Then, we illustrate a realistic dose ratio optimization of a triple combination of VRC07, 3BNC117, and 10-1074 bNAbs. We apply protection estimates derived from both a non-human primate (NHP) challenge study meta-analysis and the human antibody mediated prevention (AMP) trials. In both cases, we find a 2:1:1 dose emphasizing VRC07 is nearly optimal. Our approach can be immediately applied to optimize the next generation of combination antibody prevention and cure studies.

Indexed as

HIV-1HIV InfectionsAnimalsAntibodies, NeutralizingBroadly Neutralizing AntibodiesCombined Modality TherapyHIV AntibodiesAntibodies, NeutralizingBroadly Neutralizing AntibodiesHIV Antibodies

Identifiers

PMID35385469
PMCPMC9084525
OpenAlexW4226031698

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.